The Utility of Apparent Water Diffusion Coefficient Maps for Evaluating the Presence of Myometrial Invasion in Patients with Endometrial Cancer.

PURPOSE: To assess the utility of apparent diffusion coefficient maps (ADC) for diagnosing myometrial invasion (MI) in endometrial cancer (EC). METHODS: This retrospective study included 164 patients (mean age, 56 years; range, 25-89 years) who underwent preoperative MRI for EC with <1/2 MI or no MI between April 2016 and July 2023. Five sequences were evaluated: T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), ADC, dynamic contrast-enhanced T1-weighted imaging (DCE-T1WI), and contrast-enhanced T1WI (CE-T1WI). Three experienced radiologists independently assessed the sequences for MI. For ADC, MI was determined if the endometrial-myometrial junction-tumor boundary had disappeared. Additionally, the assessment of MI was performed using the combination of T2WI, DWI, and ADC, as well as T2WI, DCE-T1WI, and CE-T1WI. The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) for the presence of MI were calculated and compared between the sequences and combinations. Inter-reader agreement was assessed using kappa (κ) statistics. RESULTS: The sensitivity of ADC was significantly higher than T2WI (P < 0.001) and DCE-T1WI (P = 0.018) for one reader and significantly higher than CE-T1WI (P = 0.045 and 0.043) for two readers. The specificity of ADC was significantly lower than T2WI (P = 0.015 and < 0.001) and CE-T1WI (P = 0.031 and 0.01) for two readers and significantly lower than DCE-T1WI (P = 0.031) for one reader. The AUC of ADC was significantly higher than T2WI (P = 0.048) and DCE-T1WI (P = 0.049) for one reader. The combination including ADC showed higher positive predictive value for all three readers compared to any sequence or combination including contrast enhancement. Additionally, ADC demonstrated the highest agreement rates. CONCLUSION: ADC had high sensitivity for MI and the highest agreement rate among all sequences. Thus, this sequence, combined with other sequences, can be crucial for a comprehensive evaluation of MI.

Prediction of Lymph Node Metastasis in Endometrial Cancer Based on Color Doppler Ultrasound Radiomics.

RATIONALE AND OBJECTIVES: To construct a model using radiomics features based on ultrasound images and evaluate the feasibility of noninvasive assessment of lymph node status in endometrial cancer (EC) patients. METHODS: In this multicenter retrospective study, a total of 186 EC patients who underwent hysterectomy and lymph node dissection were included, Pathology confirmed the presence or absence of lymph node metastasis (LNM). The study encompassed patients from seven centers, spanning from September 2018 to November 2023, with 93 patients in each group (with or without LNM). Extracted ultrasound radiomics features from transvaginal ultrasound images, used five machine learning (ML) algorithms to establish US radiomics models, screened clinical features through univariate and multivariate logistic regression to establish a clinical model, and combined clinical and radiomics features to establish a nomogram model. The diagnostic ability of the three models for LNM with EC was compared, and the diagnostic performance and accuracy of the three models were evaluated using receiver operating characteristic curve analysis. RESULTS: Among the five ML models, the XGBoost model performed the best, with AUC values of 0.900 (95% CI, 0.847-0.950) and 0.865 (95% CI, 0.763-0.950) for the training and testing sets, respectively. In the final model, the nomogram based on clinical features and the ultrasound radiomics showed good resolution, with AUC values of 0.919 (95% CI, 0.874-0.964) and 0.884 (0.801-0.967) in the training and testing sets, respectively. The decision curve analysis verified the clinical practicality of the nomogram. CONCLUSION: The ML model based on ultrasound radiomics has potential value in the noninvasive differential diagnosis of LNM in patients with EC. The nomogram constructed by combining ultrasound radiomics and clinical features can provide clinical doctors with more comprehensive and personalized image information, which is highly important for selecting treatment strategies.

Diagnostic value of transvaginal contrastenhanced ultrasound in identifying benign and malignant endometrial lesions and assessing myometrial invasion.

PURPOSE: The objective of this study was to evaluate the diagnostic value of transvaginal contrastenhanced ultrasound (CEUS) in differentiating benign from malignant endometrial lesions and assessing the extent of myometrial invasion. METHODS: A total of 70 patients who underwent surgery for endometrial lesions at the authors' hospital were selected. Transvaginal ultrasound examination and CEUS were performed for quantitative and qualitative analysis. Based on the CEUS results, an International Federation of Gynecology and Obstetrics (FIGO) disease grade was assigned and compared with pathological findings. RESULTS: Postmenopausal vaginal bleeding is a key clinical manifestation of endometrial carcinoma. Among the patients with endometrial carcinoma, compared with normal myometrium, the lesion areas exhibited a greater rate of rise (defined as enhanced intensity divided by enhancement time) and a shorter half-clearance time (P<0.05). These findings suggest that in endometrial carcinoma, the contrast agent displays a "fast-in/fast-out/hyperenhancement" perfusion pattern. In contrast, the characteristic perfusion pattern for benign endometrial lesions is low enhancement (P<0.05). The diagnostic accuracy of CEUS in detecting myometrial invasion was 88% (22 of 25 cases). CONCLUSION: Transvaginal CEUS is a practical and effective diagnostic imaging method for distinguishing between benign and malignant endometrial lesions. It can also be used to evaluate the depth of myometrial invasion in patients with early-stage endometrial carcinoma.

Diagnostic utility of apparent diffusion coefficient in preoperative assessment of endometrial cancer: are we ready for the 2023 FIGO staging?

BACKGROUND: Although endometrial cancer (EC) is staged surgically, magnetic resonance imaging (MRI) plays a critical role in assessing and selecting the most appropriate treatment planning. We aimed to assess the diagnostic performance of quantitative analysis of diffusion-weighted imaging (DWI) in preoperative assessment of EC. METHODS: Prospective analysis was done for sixty-eight patients with pathology-proven endometrial cancer who underwent MRI and DWI. Apparent diffusion coefficient (ADC) values were measured by two independent radiologists and compared with the postoperative pathological results. RESULTS: There was excellent inter-observer reliability in measuring ADCmean values. There were statistically significant lower ADCmean values in patients with deep myometrial invasion (MI), cervical stromal invasion (CSI), type II EC, and lympho-vascular space involvement (LVSI) (AUC = 0.717, 0.816, 0.999, and 0.735 respectively) with optimal cut-off values of ≤ 0.84, ≤ 0.84, ≤ 0.78 and ≤ 0.82 mm2/s respectively. Also, there was a statistically significant negative correlation between ADC values and the updated 2023 FIGO stage and tumor grade (strong association), and the 2009 FIGO stage (medium association). CONCLUSIONS: The preoperative ADCmean values of EC were significantly correlated with main prognostic factors including depth of MI, CSI, EC type, grade, nodal involvement, and LVSI.

Training radiology residents to evaluate deep myometrial invasion in endometrial cancer patients on MRI: A learning curve study.

PURPOSE: To evaluate the impact of a four-month training program on radiology residents' diagnostic accuracy in assessing deep myometrial invasion (DMI) in endometrial cancer (EC) using MRI. METHOD: Three radiology residents with limited EC MRI experience participated in the training program, which included conventional didactic sessions, case-centric workshops, and interactive classes. Utilizing a training dataset of 120 EC MRI scans, trainees independently assessed subsets of cases over five reading sessions. Each subset consisted of 30 scans, the first and the last with the same cases, for a total of 150 reads. Diagnostic accuracy metrics, assessment time (rounded to the nearest minute), and confidence levels (using a 5-point Likert scale) were recorded. The learning curve was obtained plotting the diagnostic accuracy of the three trainees and the average over the subsets. Anatomopathological results served as the reference standard for DMI presence. RESULTS: The three trainees exhibited heterogeneous starting point, with a learning curve and a trend to more homogeneous performance with training. The diagnostic accuracy of the average trainee raised from 64 % (56 %-76 %) to 88 % (80 %-94 %) across the five subsets (p < 0.001). Reductions in assessment time (5.92 to 4.63 min, p < 0.018) and enhanced confidence levels (3.58 to 3.97, p = 0.12) were observed. Improvements in sensitivity, specificity, positive predictive value, and negative predictive value were noted, particularly for specificity which raised from 56 % (41 %-68 %) in the first to 86 % (74 %-94 %) in the fifth subset (p = 0.16). Although not reaching statistical significance, these advancements aligned the trainees with literature performance benchmarks. CONCLUSIONS: The structured training program significantly enhanced radiology residents' diagnostic accuracy in assessing DMI for EC on MRI, emphasizing the effectiveness of active case-based training in refining oncologic imaging skills within radiology residency curricula.

Multiparametric magnetic resonance imaging-based assessment of the effect of adenomyosis on determining the depth of myometrial invasion in endometrial cancer.

Background: Accurate preoperative diagnosis of endometrial cancer (EC) with deep myometrial invasion (DMI) is critical to deciding whether to perform lymphadenectomy. However, the presence of adenomyosis makes distinguishing DMI from superficial myometrial invasion (SMI) on magnetic resonance imaging (MRI) challenging. We aimed to evaluate the accuracy of multiparametric MRI (mpMRI) in diagnosing DMI in EC coexisting with adenomyosis (EC-A) compared with EC without coexisting adenomyosis and to evaluate the effect of different adenomyosis subtypes on myometrial invasion (MI) depth in EC. Methods: Patients with histologically confirmed International Federation of Gynecology and Obstetrics (FIGO) stage I EC who underwent preoperative MRI were consecutively included in this 2-center retrospective study. Institution 1 was searched from January 2017 to November 2022 and institution 2 was searched from June 2017 to March 2021. Patients were divided into 2 groups: group A, patients with EC-A; group B, EC patients without coexisting adenomyosis, matched 1:2 according to age ±5 years and tumor grade. A senior radiologist assessed the MRI adenomyosis classification in group A. Then, 2 radiologists (R1/R2) independently interpreted T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), T1-weighted contrast-enhanced (T1CE), and a combination of all images (mpMRI) respectively, and then assessed MI depth. Accuracy, sensitivity, specificity, and the areas under the receiver operating curve (AUC) were calculated. The chi-square test was used to compare the accuracy of diagnosing DMI. Interobserver agreement was evaluated using the Kappa test. Results: A total of 70 cases in group A and 140 cases in group B were included. The accuracy, sensitivity, and specificity of consensus were 94.3% [95% confidence interval (CI): 88.9-99.7%] vs. 92.1% (95% CI: 87.7-96.6%), 60.0% (95% CI: 17-92.7%) vs. 86.7% (95% CI: 68.4-95.6%), and 96.9% (95% CI: 88.4-95.5%) vs. 93.6% (95% CI: 86.8-97.2%) (group A vs. group B, respectively). There was no significant difference in the diagnostic accuracy of DMI on each sequence between the groups (Reviewer 1/Reviewer 2): PT2WI=0.14/0.17, PDWI=0.50/0.33, PT1CE=0.90/0.18, PmpMRI=0.50/0.37. The AUC for T2WI, DWI, T1CE, and mpMRI (Reviewer 1/Reviewer 2), respectively, were 0.54 (95% CI: 0.42-0.66)/0.78 (95% CI: 0.67-0.87), 0.63 (95% CI: 0.50-0.74)/0.77 (95% CI: 0.65-0.86), 0.69 (95% CI: 0.57-0.80)/0.79 (95% CI: 0.68-0.88), and 0.91 (95% CI: 0.82-0.97)/0.89 (95% CI: 0.79-0.95) (group A) and 0.83 (95% CI: 0.76-0.89)/0.85 (95% CI: 0.78-0.90), 0.83 (95% CI: 0.76-0.89)/0.86 (95% CI: 0.79-0.91), 0.88 (95% CI: 0.82-0.93)/0.86 (95% CI: 0.80-0.92), and 0.91 (95% CI: 0.85-0.95)/0.87 (95% CI: 0.80-0.92) (group B). Interobserver agreement was highest with mpMRI [κ=0.387/0.695 (case/control)]. The consensus results of MRI categorization of adenomyosis revealed no significant difference in the accuracy of diagnosing DMI by adenomyosis subtype (Pspatial relationship>0.99, Paffected area=0.52, Paffected pattern=0.58, Paffected size>0.99). Conclusions: The presence of adenomyosis or adenomyosis subtype had no significant effect on the interpretation of the depth of MI. T1CE can increase the contrast between adenomyosis and cancer foci; therefore, the information provided by T1CE should be valued.

Risk assessment of extra-uterine involvement and prognosis in young type I endometrial carcinoma with high or moderate differentiation and less than 1/2 myometrial invasion.

PURPOSE: The aim of this study was to investigate whether young patients with endometrial carcinoma can preserve adnexa and lymph nodes to improve their quality of life without compromising their prognosis. METHODS: A total of 319 patients with type I endometrial carcinoma (high or moderate differentiation and less than 1/2 myometrial invasion) hospitalized in the First Affiliated Hospital of Zhengzhou University from May 2012 to July 2021 were included. The patients were divided into four groups: high differentiation without myometrial invasion group (G1MI-), high differentiation with superficial myometrial invasion group (G1MI+), moderate differentiation without myometrial invasion group (G2MI-), and moderate differentiation with superficial myometrial invasion group (G2MI+). Logistic regression analysis was conducted to identify risk factors for extra-uterine involvement. Kaplan-Meier method was used to draw the survival curve to compare the prognosis in subgroups and rates of extra-uterine involvement were also compared using Chi-square test or Fisher's exact test. RESULTS: Multivariable logistic regression revealed that differentiation (HR = 14.590, 95%CI = 1.778-119.754, p = 0.013) and myometrial invasion (HR = 10.732, 95%CI = 0.912-92.780, p = 0.037) were the independent risk factors for extra-uterine involvement. The overall difference was statistically significant (p < 0.001). In the subgroups analysis, both adnexal metastasis and lymph node metastasis were statistically significant in the G2MI+ group compared with G1MI- (p = 0.007, p = 0.008). There were no significant differences in the overall survival (OS) rate and progression free survival (PFS) rate among the four subgroups (p > 0.05). CONCLUSIONS: Surgery with adnexal preservation and without systematic lymphadenectomy could be employed for the patients who are high differentiation with less than 1/2 myometrial invasion or moderate differentiation without myometrial invasion, but not recommended to the patients with moderate differentiation and superficial myometrial invasion.

Can the ADC Value Be Used as an Imaging "Biopsy" in Endometrial Cancer?

BACKGROUND: The tumor histological grade is closely related to the prognosis of patients with endometrial cancer (EC). Multiparametric MRI, including diffusion-weighted imaging (DWI), provides information about the cellular density that may be useful to differentiate between benign and malignant uterine lesions. However, correlations between apparent diffusion coefficient (ADC) values and histopathological grading in endometrial cancer remain controversial. MATERIAL AND METHODS: We retrospectively evaluated 92 patients with endometrial cancers, including both endometrioid adenocarcinomas (64) and non-endometrioid adenocarcinomas (28). All patients underwent DWI procedures, and mean ADC values were calculated in a region of interest. These values were then correlated with the tumor grading offered by the histopathological examination, which was considered the gold standard. In this way, the patients were divided into three groups (G1, G2, and G3). The ADC values were then compared to the results offered by the biopsy to see if the DWI sequence and ADC map could replace this procedure. We also compared the mean ADC values to the myometrial invasion (50%) and lymphovascular space invasion. RESULTS: We have divided the ADC values into three categories corresponding to three grades: >0.850 × 10-3 mm2/s (ADC1), 0.730-0.849 × 10-3 mm2/s (ADC2) and <0.730 × 10-3 mm2/s (ADC3). The diagnostic accuracy of the ADC value was 85.71% for ADC1, 75.76% for ADC2, and 91.66% for ADC3. In 77 cases out of 92, the category in which they were placed using the ADC value corresponded to the result offered by the histopathological exam with an accuracy of 83.69%. For only 56.52% of patients, the biopsy result included the grading system. For each grading category, the mean ADC value showed better results than the biopsy; for G1 patients, the mean ADC value had an accuracy of 85.71% compared to 66.66% in the biopsy, G2 had 75.76% compared to 68.42%, and G3 had 91.66 compared to 75%. For both deep myometrial invasion and lymphovascular space invasion, there is a close, inversely proportional correlation with the mean ADC value. CONCLUSIONS: Mean endometrial tumor ADC on MR-DWI is inversely related to the histological grade, deep myometrial invasion and lymphovascular space invasion. Using this method, the patients could be better divided into risk categories for personalized treatment.

A Transvaginal Ultrasound-Based Deep Learning Model for the Noninvasive Diagnosis of Myometrial Invasion in Patients with Endometrial Cancer: Comparison with Radiologists.

RATIONALE AND OBJECTIVES: This study aimed to determine the feasibility of using the deep learning (DL) method to determine the degree (whether myometrial invasion [MI] >50%) of MI in patients with endometrial cancer (EC) based on ultrasound (US) images. MATERIALS AND METHODS: From September 2017 to April 2023, 1289 US images of 604 patients with EC who underwent surgical resection at center 1, center 2 or center 3 were obtained and divided into a training set and an internal validation set. Ninety-five patients from center 4 and center 5 were randomly selected as the external testing set according to the same criteria as those for the primary cohort. This study evaluated three DL models trained on the training set and tested them on the validation and testing sets. The models' performance was analyzed based on accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC), and the performance of the models was subsequently compared with that of 15 radiologists. RESULTS: In the final clinical diagnosis of MI in patients with EC, EfficientNet-B6 showed the best performance in the testing set in terms of area under the curve (AUC) [0.814, 95% CI (0.746-0.882]; accuracy [0.802, 95% CI (0.733-0.855]; sensitivity [0.623]; specificity [0.879]; positive likelihood ratio (PLR) [6.750]; and negative likelihood ratio (NLR) [0.389]. The diagnostic efficacy of EfficientNet-B6 was significantly better than that of the 15 radiologists, with an average diagnostic accuracy of 0.681, average AUC of 0.678, AUC of the best performance of 0.739, accuracy of 0.716, sensitivity of 0.806, specificity 0.672, PLR2.457, and NLR 0.289. CONCLUSION: Based on the preoperative US images of patients with EC, the DL model can accurately determine the degree of endometrial MI; the performance of this model is significantly better than that of radiologists, and it can effectively assist in clinical treatment decisions.

Retrospective analysis of the 18F-FDG PET/CT cutoff value for metabolic parameters was performed as a prediction model to evaluate risk factors for endometrial cancer.

PURPOSE: The study retrospectively analyzed the accuracy and predictive ability of preoperative integrated whole-body 18F-FDG PET/CT for the assessment of high-risk factors in patients with endometrial carcinoma (EC). MATERIALS AND METHODS: A total of 205 patients with endometrial cancer who underwent preoperative PET/CT at Shanghai General Hospital from January 2018 to December 2021 were retrospectively evaluated and last follow-up was June 2023. Our study evaluated the ability and optimal cutoff values of three metabolic and volumetric parameters-standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG)-to predict deep myometrial invasion (DMI), endocervical stroma invasion (ESI) and lymph node metastases (LNM) in endometrial cancer. The accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of PET/CT were used to assess the diagnostic performance for the prediction. RESULTS: Our study demonstrated a significant relationship between SUVmax (11.29, 17.38, 9.47), SUVmean (5.20, 6.12, 4.49), MTV (38.15, 36.28, 33.79 ml), and TLG (199.30, 225.10, 156.40 g) on PET/CT and histologically confirmed DMI, ESI and LNM in endometrial carcinoma (EC), with sensitivity, specificity, accuracy, PPV, and NPV of 100%/100%/100%, 96.53%/98.89%/87.14%, 97.56%/99.02%/91.22%, 92.42%/92.85%/78.31%, and 100%/100%/100%, respectively. Our study showed a risk model based on optimal cutoff values for MTV and TLG of 19.6 ml/126.3 g, 20.54 ml/84.80 g and 24 ml/49.83 g to preoperatively predict DMI, ESI, and LNM, respectively, in endometrial carcinoma. The 4-year OS (HR) for Stage IA, IB, II, III and IV according to 2009 FIGO was 98.00% (0.22), 95.20% (0.04), 83.90% (0.18), 90.50% (0.09) and 60% (0.51). Accordingly, estimated 4-year DFS (HR) for the stage IA-III was 98% (0.02), 95.20% (0.05), 76.90% (0.27) and 76.30% (0.35), all the patients in stage IV occurred recurrence and progression. CONCLUSION: The present study showed patients with MTV > = 19.6 ml of MI and PET- positive LN with MTV cutoff > = 24 ml tended to predict poor OS and PFS in endometrial carcinoma. The cutoff of MTV and TLG in PET/CT assessment could be an independent prognostic factors to predict aggressive forms of EC.

The Added Value of ADC-based Nomogram in Assessing the Depth of Myometrial Invasion of Endometrial Endometrioid Adenocarcinoma.

RATIONALE AND OBJECTIVES: To explore the potential value of the apparent diffusion coefficient (ADC)-based nomogram models in preoperatively assessing the depth of myometrial invasion of endometrial endometrioid adenocarcinoma (EEA). MATERIALS AND METHODS: Preoperative magnetic resonance imaging (MRI) of 210 EEA patients were retrospectively analyzed. ADC histogram metrics derive from the whole-tumor regions of interest. Univariate and multivariate analyses were used to screen the ADC histogram metrics and clinical characteristics for nomogram model building. The diagnostic sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of two radiologists without and with the assistance of models were calculated and compared. RESULTS: Two nomogram models were developed for predicting no myometrial invasion (NMI) and deep myometrial invasion (DMI) with area under the curves of 0.85 and 0.82, respectively. With the assistance of models, the overall accuracies were significantly improved [radiologist_1, 73.3% vs 86.2% (p = 0.001); radiologist_2, 80.0% vs 91.0% (p = 0.002)]. In determining NMI, the sensitivity and PPV were greatly improved but not significant for radiologist_1 (51.9% vs 77.8% and 46.7% vs 75.0%, p = 0.229 and 0.511), and under/near the significance level for radiologist_2 (59.3% vs 88.9% and 57.1% vs 82.8%, p = 0.041 and 0.065), while the specificity, accuracy, and NPV were significantly improved (all p < 0.001). In determining DMI, all sensitivity, specificity, accuracy, PPV, and NPV were significantly improved (all p < 0.001). CONCLUSION: The ADC-based nomogram models can improve the diagnostic performance of radiologist in preoperatively assessing the depth of myometrial invasion and facilitate optimizing clinical individualized treatment decisions.

Contrast-Enhanced MRI in Women with Endometrial Cancer: Dynamic Versus Single-Phase Acquisitions.

Background: The 2019 European Society of Urogenital Radiology (ESUR) guidelines for endometrial cancer recommend performing either dynamic contrast-enhanced magnetic resonance imaging (CE MRI) or single-phase CE MRI. However, no study has directly compared these options. Therefore, this study compared dynamic versus single-phase CE MRI for the evaluation of myometrial invasion in women with endometrial cancer. Methods: This retrospective, single-institution comparative study was conducted among women with surgically proven endometrial cancer, including 30 consecutive women with single-phase CE MRI and 30 age- and pathologic stage-matched women with dynamic CE MRI. Three readers independently compared dynamic and single-phase CE MRI in terms of the tumor-myometrium signal intensity (SI) difference ratio, depth of myometrial invasion, image quality, and image number. Pathologic findings served as a reference standard for the depth of myometrial invasion. Results: The estimated mean SI difference ratios of dynamic CE MRI and single-phase CE MRI fell within an equivalence margin of 0.05 (90% confidence intervals [CIs] = [-0.0497 to -0.0165], [-0.0226 to -0.0403], and [-0.0429 to -0.0433], respectively, for readers A, B, and C). The area under the receiver operating characteristic curve for the detection of deep myometrial invasion was not significantly different between the acquisitions (P = .3315, P = .3345, and P = .8593, respectively). Single-phase CE MRI showed significantly better image quality than dynamic CE MRI (P = .0143, P = .0042, and P = .0066, respectively), while the median number of images for dynamic CE MRI was 2.4 times higher than that for single-phase CE MRI. Conclusion: Single-phase acquisition may be a better option for CE MRI in women with endometrial cancer than dynamic acquisition.

The association of polypoid growth pattern with lymph node involvement in endometrioid type endometrial adenocarcinoma.

Background: Tumor size is an independent predictor of lymph node metastasis and survival in the endometrioid type endometrial adenocarcinoma (EC). However, some of the ECs tend to grow towards the cavity in the polypoid pattern, which can reach very large sizes. In this study, we aimed to analyze the association of growing in the polypoid pattern of the tumor with the proportion of lymph node metastasis and extrauterine tumor spread. Methods: Four hundred seven patients were analyzed retrospectively. The effect of tumor size, tumor growing pattern, myometrial invasion, grade, and lymphovascular space invasion on the lymph node metastasis and extrauterine tumor spread were investigated. Statistical analysis consisted of unpaired t-tests for parametric data and Mann Whitney-U test for non-parametric data, whereas the Chi-square test for categorical variables. Logistic Regression, Cox Regression and multivariate analysis were used to estimate the risk predictors. Results: No association was found between the growing in polypoid pattern and lymph node metastasis (P > 0.05). In the analysis of endometrioid type EC patients who had myometrial invasion less than ½ as a subgroup, no association was found between the growing pattern and lymph node metastasis and extrauterine disease. Tumor size was found to be a statistically significant predictor of lymph node metastasis and extrauterine disease (P < 0.05). Conclusions: Lymphovascular space invasion, grade, and myometrial invasion are associated with a higher proportion of lymph node metastasis. The polypoid growth pattern of the tumor does not correlate with any histopathological parameters.

Preoperative staging of uterine cancer: can transvaginal ultrasonography play a role?

Introduction: Preoperative staging of uterine cancer has recently been implied as an important contribution to an accurate selection of low-risk cases, ultimately avoiding unnecessary lymph node debulking. The aim of this study was to evaluate the validity of transvaginal ultrasonography (TVS) in preoperative staging of uterine cancer in comparison to pelvic magnetic resonance imaging (MRI) and permanent section. Methods: We conducted a prospective longitudinal multicenter trial between 2017 and 2018. Inclusion criteria comprised cases of endometrial neoplasia histologically confirmed or strong imaging suspicion, candidates for elective surgery as primary treatment. Proportions of Agreement (PA), kappa statistic (K), sensitivity, specificity and accuracy were calculated with 95% confidence intervals (95%CI). Results: Eighty-two patients were eligible for the study, presenting a mean age of 68 years (standard deviation 11). In what concerns the TVS evaluation of myometrial invasion, the subjective and objective methods of Gordon and Karlsson presented a sensitivity of 79%, 79% and 67% [95%CI 63-91; 63-91; 50-81], a specificity of 65%, 58% and 79% [95%CI 49-79; 42-73; 64-89] and an overall accuracy of 72%, 68% and 73% [95%CI 61-81; 57-78; 63-82]. MRI presented respectively a sensitivity, specificity and overall accuracy of 92%, 70% and 82% [95%CI 77-98; 52-85; 71-90]. Regarding cervical involvement, the sensitivity was respectively 31%, 50% and 67% [95%CI 9-61; 21-79; 35-90] for the subjective method, objective TVS and MRI, and the specificity was 98%, 90% and 100% [95%CI 92-100; 77-97; 94;100]. Agreement between TVS and MRI was superior in the assessment of cervical invasion, with PA ranging from 0.82 to 0.93 and K from 0.45 to 0.58, in comparison to myometrial invasion with PA ranging from 0.68 to 0.73 and K from 0.31 to 0.50. Considering the assessment of cervical involvement, as MRI showed a specificity of 100% it is not possible to increase the specificity. However, it was possible to increase the sensitivity, considering the combination of TVS with objective approach and MRI. Conclusion: TVS may have a promising role as a tool for preoperative staging of endometrial carcinoma, presenting a performance that approximates to MRI, with a higher agreement in the assessment of cervical invasion.

Study on the preoperative value of serum SCC-Ag in predicting the stromal invasion of cervical squamous cell carcinoma.

OBJECTIVE: To investigate the preoperative value of serum SCC-Ag in predicting the stromal invasion of cervical squamous cell carcinoma. METHODS: This study retrospectively analyzed 78 patients with early cervical squamous cell carcinoma who underwent surgery as initial treatment at the Senior Department of Obstetrics and Gynecology, the Seventh Medical Center of PLA General Hospital from January 2018 to September 2022 was implemented. The clinicopathological characteristics were statistically compared. The ROC curve was drawn to determine the optimal critical level of  preoperative serum SCC-Ag value for predicting cervical stromal invasion. RESULTS: The depth of myometrial invasion was not related to the age of diagnosis and HPV infection (p > 0.05), while it was related to tumor size, staging, tissue differentiation, LVSI, lymph node metastasis (LNM) and preoperative serum SCC-Ag value (p < 0.05).The area under the curve (AUC) of serum SCC-Ag value was 0.894 (p = 0.000, 95% CI 0.824-0.964), and preoperative serum SCC-Ag value 1.65 ng/ml was the best cutoff for predicting cervical stromal invasion in cervical squamous cell carcinoma. The sensitivity and specificity of diagnosis were 92.3% and 78.8%, respectively. CONCLUSION: If the preoperative serum SCC-Ag leval more than 1.65 ng/ml in patients with cervical squamous cell carcinoma, the risk of cervical stromal invasion will increase, which can provide a reference for clinical treatment.

Metabolic risk score as a predictor in a nomogram for assessing myometrial invasion for endometrial cancer.

The purpose of the present study was to investigate the predictive value of metabolic syndrome in evaluating myometrial invasion (MI) in patients with endometrial cancer (EC). The study retrospectively included patients with EC who were diagnosed between January 2006 and December 2020 at the Department of Gynecology of Nanjing First Hospital (Nanjing, China). The metabolic risk score (MRS) was calculated using multiple metabolic indicators. Univariate and multivariate logistic regression analyses were performed to determine significant predictive factors for MI. A nomogram was then constructed based on the independent risk factors identified. A calibration curve, a receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to evaluate the effectiveness of the nomogram. A total of 549 patients were randomly assigned to a training or validation cohort, with a 2:1 ratio. Data was then gathered on significant predictors of MI in the training cohort, including MRS [odds ratio (OR), 1.06; 95% confidence interval (CI), 1.01-1.11; P=0.023], histological type (OR, 1.98; 95% CI, 1.11-3.53; P=0.023), lymph node metastasis (OR, 3.15; 95% CI, 1.61-6.15; P<0.001) and tumor grade (grade 2: OR, 1.71; 95% CI, 1.23-2.39; P=0.002; Grade 3: OR, 2.10; 95% CI, 1.53-2.88; P<0.001). Multivariate analysis indicated that MRS was an independent risk factor for MI in both cohorts. A nomogram was generated to predict a patient's probability of MI based on the four independent risk factors. ROC curve analysis showed that, compared with the clinical model (model 1), the combined model with MRS (model 2) significantly improved the diagnostic accuracy of MI in patients with EC (area under the curve in model 1 vs. model 2: 0.737 vs. 0.828 in the training cohort and 0.713 vs. 0.759 in the validation cohort). Calibration plots showed that the training and validation cohorts were well calibrated. DCA showed that a net benefit is obtained from the application of the nomogram. Overall, the present study developed and validated a MRS-based nomogram predicting MI in patients with EC preoperatively. The establishment of this model may promote the use of precision medicine and targeted therapy in EC and has the potential to improve the prognosis of patients affected by EC.

It is not the time to abandon intraoperative frozen section in endometrioid adenocarcinoma: A large-scale, multi-center, and retrospective study.

INTRODUCTION: Stage IB (deep myometrial invasion) high-grade endometrioid adenocarcinoma (EA), regardless of LVSI status, is classified into high-intermediate risk groups, requiring surgical lymph node staging. Intraoperative frozen section (IFS) is commonly used, but its adequacy and reliability vary between reports. Hence, we determined the utility of IFS in identification of high-risk factors, including deep myometrial invasion and high-grade. METHOD: We retrospectively analyzed 9,985 cases operated with hysterectomy and diagnosed with FIGO stage I/II EA in postoperative paraffin section (PS) results at 30 Chinese hospitals from 2000 to 2019. We determined diagnostic performance of IFS and investigated whether the addition of IFS to preoperative biopsy and imaging could improve identification of high-risk factors. RESULTS: IFS and postoperative PS presented the highest concordance in assessing deep myometrial invasion (Kappa: 0.834), followed by intraoperative gross examination (IGE Kappa: 0.643), MRI (Kappa: 0.395), and CT (Kappa: 0.207). IFS and postoperative PS presented the highest concordance for high-grade EA (Kappa: 0.585) compared to diagnostic curettage (D&C 0.226) and hysteroscope (Hys 0.180). Sensitivity and specificity for detecting deep myometrial invasion were 86.21 and 97.20% for IFS versus 51.72 and 88.81% for MRI, 68.97 and 94.41% for IGE. These figures for detecting high-grade EA were 58.21 and 96.50% for IFS versus 16.42 and 98.83% for D&C, 13.43 and 98.64% for Hys. Parallel strategies, including MRI-IFS (Kappa: 0.626), D&C-IFS (Kappa: 0.595), and Hys-IFS (Kappa: 0.578) improved the diagnostic efficiencies of individual preoperative examinations. Based on the high sensitivity of IFS, parallel strategies improved the sensitivities of preoperative examinations to 89.66% (MRI), 64.18% (D&C), 62.69% (Hys), respectively, and these differences were statistically significant (p = 0.000). CONCLUSION: IFS presented reasonable agreement rates predicting postoperative PS results, including deep myometrial invasion and high-grade. IFS helps identify high-intermediate risk patients in preoperative biopsy and MRI and guides intraoperative lymphadenectomy decisions in EA.

Preoperative and intraoperative assessment of myometrial invasion in patients with FIGO stage I non-endometrioid endometrial carcinoma-a large-scale, multi-center, and retrospective study.

INTRODUCTION: Myometrial invasion is a prognostic factor for lymph node metastases and decreased survival in non-endometrioid endometrial carcinoma patients. Herein, we explored the mode of myometrial invasion diagnosis in FIGO stage I non-endometrioid carcinoma and evaluated the differences in diagnostic efficiency among intraoperative frozen section (IFS), intraoperative gross examination (IGE), magnetic resonance imaging (MRI), and computed tomography (CT) in clinical practice. Finally, we suggested which test should be routinely performed. METHOD: This was a historical cohort study nationwide with 30 centers in China between January 2000 and December 2019. Clinical data, including age, histology, method of myometrial invasion evaluation (MRI, CT, IGE, and IFS), and final diagnosis of postoperative paraffin sections, were collected from 490 non-endometrioid endometrial carcinoma (serous, clear cell, undifferentiated, mixed carcinoma, and carcinosarcoma) women in FIGO stage I. RESULTS: Among the 490 patients, 89.59% presented myometrial invasion. The methods reported for myometrial invasion assessment were IFS in 23.47%, IGE in 69.59%, MRI in 37.96%, and CT in 10.20% of cases. The highest concordance was detected between IFS and postoperative paraffin sections (Kappa = 0.631, accuracy = 93.04%), followed by IGE (Kappa = 0.303, accuracy = 82.40%), MRI (Kappa = 0.131, accuracy = 69.35%), and CT (Kappa = 0.118, accuracy = 50.00%). A stable diagnostic agreement between IFS and the final results was also found through the years (2000-2012: Kappa = 0.776; 2013-2014: Kappa = 0.625; 2015-2016: Kappa = 0.545; 2017-2019: Kappa = 0.652). CONCLUSION: In China, the assessment of myometrial invasion in non-endometrioid endometrial carcinoma is often performed via IGE, but the reliability is relatively low in contrast to IFS. In clinical practice, IFS is a reliable method that can help accurately assess myometrial invasion and intraoperative decision-making (lymph node dissection or not). Hence, it should be routinely performed in non-endometrioid endometrial carcinoma patients.

Development and Validation of an MRI-based Radiomics Nomogram for Assessing Deep Myometrial Invasion in Early Stage Endometrial Adenocarcinoma.

RATIONALE AND OBJECTIVES: To establish a radiomics nomogram for detecting deep myometrial invasion (DMI) in early stage endometrioid adenocarcinoma (EAC). MATERIALS AND METHODS: A total of 266 patients with stage I EAC were divided into training (n = 185) and test groups (n = 81). Logistic regression were used to identify clinical predictors. Radiomics features were extracted and selected from multiparameter MR images. The important clinical factors and radiomics features were integrated into a nomogram. A receiver operating characteristic curve was used to evaluate the nomogram. Two radiologists evaluated MR images with or without the help of the nomogram to detect DMI. The clinical benefit of using the nomogram was evaluated by decision curve analysis (DCA) and by calculating net reclassification index (NRI) and integrated discrimination index (IDI). RESULTS: Age and CA125 were independent clinical predictors. The area under the curves of the clinical parameters, radiomics signature and nomogram in evaluating DMI were 0.744, 0.869 and 0.883, respectively. The accuracies of the two radiologists increased from 79.0% and 80.2% to 90.1% and 92.5% when they used the nomogram. The NRI of the two radiologists were 0.262 and 0.318, and the IDI were 0.322 and 0.405. According to DCA, the nomogram showed a higher net benefit than the radiomics signature or unaided radiologists. Cross-validation showed the outcome of radiomics analysis may not be influenced by changes in field strength. CONCLUSION: The radiomics nomogram based on radiomics features and clinical factors can help radiologists evaluate DMI and improve their accuracy in predicting DMI in early stage EAC.

Significance of positive peritoneal cytology for recurrence and survival in patients with endometrial cancer.

AIM: This study aims to examine the association between malignant peritoneal cytology and prognosis in women with endometrial cancer. METHODS: We retrospectively analyzed the records of patients with endometrial cancer who underwent surgery with intraoperative peritoneal cytology at our hospital between January 1988 and December 2012. All results were reclassified according to the 2009 International Federation of Gynecology and Obstetrics (FIGO) system, and the relation between intraoperative peritoneal cytology results and recurrence and prognosis was examined. RESULTS: Of the 908 patients analyzed, 205 (22.6%) had positive peritoneal cytology. Patients with positive peritoneal cytology had significantly lower rates of recurrence-free survival (RFS) and overall survival (OS) than those in the negative cytology group (both p < 0.001). Subgroup analysis of patients with FIGO stage I/II showed significantly lower RFS in the positive-cytology group (p = 0.005), but there was no significant difference in OS (p = 0.637). In the patients with FIGO stage III/IV or patients classified as "high risk," the RFS and OS were significantly lower in the positive-cytology group (both p < 0.001). Cox regression analysis identified positive peritoneal cytology as a significant predictor of recurrence in patients with FIGO stage I/II disease. CONCLUSIONS: Patients with positive peritoneal cytology for endometrial cancer have a high risk of recurrence, regardless of histopathologic type or FIGO stage. Peritoneal cytology has already been removed from the 2009 FIGO classification of endometrial cancer, but it may deserve reconsideration.